Creating Features for Time Series Data

Statistical Analysis System, widely known as SAS, is a leading analytics and AI software company established in 1976 that supports organizations across healthcare, finance, government, and academia. While not a traditional university, SAS plays a major educational role through its analytics platforms, research collaborations, and partnerships with colleges and universities. Its tools are used for statistical analysis, predictive modeling, machine learning, and enterprise intelligence.

For international students pursuing data science, analytics, or related fields, SAS offers a range of learning pathways including certification programs, instructor-led courses, online training, and academic alliances with more than 40 program tracks and learning modules. These resources are designed to develop practical skills in real-world problem solving, from data preparation and visualization to advanced modeling and deployment. Students can access hands-on labs, community forums, and sanctioned curricula that align with industry expectations.

Engagement with SAS technologies can significantly enhance employability in a competitive job market where analytics expertise is in demand. Prospective learners should explore university partnerships, internship opportunities, and certification routes that complement degree programs. International applicants can benefit from SAS learning resources to build portfolios, demonstrate technical competence to employers, and transition more smoothly into analytics roles globally.

The Creating Features for Time Series Data program is for students who want to learn about time series data features. It's a non-degree program that lasts several weeks and is taught in English. The main advantage of this program is that it's online and helps students learn new skills.

This program covers specific subjects like feature creation for time series data. Students will develop skills in data preprocessing and learn how to create features for time series data. The program includes hands-on components to help students practice their skills.

After completing this program, students can pursue careers like Data Scientist, Machine Learning Engineer, or Data Engineer. They can work in industries like finance, technology, or research for employers like startups or government agencies.